This is the RMarkdown for Exam 3. Below, we will analyze the BioLogData.
## Sample.ID Rep Well Dilution Substrate Hr_24 Hr_48 Hr_144
## 1 Clear_Creek 1 A1 0.001 Water 0.000 0.000 0.000
## 2 Clear_Creek 1 A2 0.001 β-Methyl-D- Glucoside 0.004 0.005 0.004
## 3 Clear_Creek 1 A3 0.001 D-Galactonic Acid γ-Lactone 0.008 0.007 0.001
## 4 Clear_Creek 1 A4 0.001 L-Arginine 0.003 0.002 0.000
## 5 Clear_Creek 1 B1 0.001 Pyruvic Acid Methyl Ester 0.002 0.000 0.007
## 6 Clear_Creek 1 B2 0.001 D-Xylose 0.011 0.008 0.021
| Column ID | Description |
|---|---|
| Sample.ID | The location the sample was taken from. There are 2 water samples and 2 soil samples. |
| Rep | The experimental replicate. 3 replicates for each combination of experimental variables. |
| Well | The well number on the BioLog plate. |
| Dilution | The dilution factor of the sample. |
| Substrate | The name of the carbon source in that well. “Water” is the negative control. |
| Hr_24 | The light absorbance value after 24 hours of incubation. |
| Hr_48 | The light absorbance value after 48 hours of incubation. |
| Hr_144 | The light absorbance value after 144 hours of incubation. |
It looks like we need to do some re-arranging of some columns. We’ll do some subsetting and tidying in a bit.
What are the classes of each column?
## Sample.ID Rep Well Dilution Substrate Hr_24 Hr_48 Hr_144
## "factor" "integer" "factor" "numeric" "factor" "numeric" "numeric" "numeric"
## Sample.ID Rep Well Dilution
## Clear_Creek:288 Min. :1 A1 : 36 Min. :0.001
## Soil_1 :288 1st Qu.:1 A2 : 36 1st Qu.:0.001
## Soil_2 :288 Median :2 A3 : 36 Median :0.010
## Waste_Water:288 Mean :2 A4 : 36 Mean :0.037
## 3rd Qu.:3 B1 : 36 3rd Qu.:0.100
## Max. :3 B2 : 36 Max. :0.100
## (Other):936
## Substrate Hr_24 Hr_48
## 2-Hydroxy Benzoic Acid : 36 Min. :0.0000 Min. :0.0000
## 4-Hydroxy Benzoic Acid : 36 1st Qu.:0.0000 1st Qu.:0.0060
## D-Cellobiose : 36 Median :0.0320 Median :0.2595
## D-Galactonic Acid γ-Lactone: 36 Mean :0.1703 Mean :0.4691
## D-Galacturonic Acid : 36 3rd Qu.:0.1872 3rd Qu.:0.7220
## D-Glucosaminic Acid : 36 Max. :2.6500 Max. :2.7850
## (Other) :936
## Hr_144
## Min. :0.00000
## 1st Qu.:0.04175
## Median :0.75200
## Mean :0.92497
## 3rd Qu.:1.67950
## Max. :3.11600
##
## [1] Clear_Creek Soil_1 Soil_2 Waste_Water
## Levels: Clear_Creek Soil_1 Soil_2 Waste_Water
## [1] Water β-Methyl-D- Glucoside
## [3] D-Galactonic Acid γ-Lactone L-Arginine
## [5] Pyruvic Acid Methyl Ester D-Xylose
## [7] D-Galacturonic Acid L-Asparganine
## [9] Tween 40 i-Erythitol
## [11] 2-Hydroxy Benzoic Acid L-Phenylalanine
## [13] Tween 80 D-Mannitol
## [15] 4-Hydroxy Benzoic Acid L-Serine
## [17] α-Cyclodextrin N-Acetyl-D-Glucosamine
## [19] γ-Hydroxybutyric Acid L-Threonine
## [21] Glycogen D-Glucosaminic Acid
## [23] Itaconic Acid Glycyl-L-Glutamic Acid
## [25] D-Cellobiose Glucose-1-Phosphate
## [27] α-Ketobutyric Acid Phenylethylamine
## [29] α-D-Lactose D.L -α-Glycerol Phosphate
## [31] D-Mallic Acid Putrescine
## 32 Levels: 2-Hydroxy Benzoic Acid 4-Hydroxy Benzoic Acid ... γ-Hydroxybutyric Acid
creek <- creek %>%
mutate(status="water")
wastewater <- wastewater %>%
mutate(status="water")
soil1 <- soil1 %>%
mutate(status="soil")
soil2 <- soil2 %>%
mutate(status="soil")
df <- rbind(creek, wastewater, soil1, soil2)
## Df Sum Sq Mean Sq F value Pr(>F)
## Substrate 31 143.0 4.61 12.484 < 2e-16 ***
## status 1 237.2 237.20 641.878 < 2e-16 ***
## Substrate:status 31 42.1 1.36 3.674 3.55e-11 ***
## Residuals 3392 1253.5 0.37
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mod2 <- aov(data=creek, values ~ Substrate * Dilution)
plot(creek$values ~ creek$Dilution)
summary(mod2)
## Df Sum Sq Mean Sq F value Pr(>F)
## Substrate 31 11.01 0.355 2.744 1.56e-06 ***
## Dilution 1 16.75 16.748 129.373 < 2e-16 ***
## Substrate:Dilution 31 17.06 0.550 4.251 4.22e-13 ***
## Residuals 800 103.57 0.129
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mod3 <- aov(data=wastewater, values ~ Substrate * Dilution)
plot(wastewater$values ~ wastewater$Dilution)
summary(mod3)
## Df Sum Sq Mean Sq F value Pr(>F)
## Substrate 31 35.51 1.146 5.215 < 2e-16 ***
## Dilution 1 12.74 12.740 58.000 7.40e-14 ***
## Substrate:Dilution 31 18.78 0.606 2.758 1.37e-06 ***
## Residuals 800 175.72 0.220
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mod4 <- aov(data=soil1, values ~ Substrate * Dilution)
plot(soil1$values ~ soil1$Dilution)
summary(mod4)
## Df Sum Sq Mean Sq F value Pr(>F)
## Substrate 31 88.1 2.841 5.320 < 2e-16 ***
## Dilution 1 21.4 21.410 40.090 4.04e-10 ***
## Substrate:Dilution 31 10.1 0.325 0.609 0.955
## Residuals 800 427.2 0.534
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mod5 <- aov(data=soil2, values ~ Substrate * Dilution)
plot(soil2$values ~ soil2$Dilution)
summary(mod5)
## Df Sum Sq Mean Sq F value Pr(>F)
## Substrate 31 74.6 2.41 5.53 <2e-16 ***
## Dilution 1 54.0 53.99 124.14 <2e-16 ***
## Substrate:Dilution 31 17.4 0.56 1.29 0.136
## Residuals 800 347.9 0.43
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1